Heart electrophysiological signal analysis system

ABSTRACT

A system automatically detects and measures ST deviation of a heart wave ECG signal in the presence of noise and accommodates baseline variation of the signal and other artifacts. A system identifies a particular point in an electrophysiological signal representing heart electrical activity using an interface for receiving an electrical signal waveform comprising an R-wave and including an ST segment portion associated with heart electrical activity of a patient over a heart beat cycle. A signal processor processes data representing the electrical signal waveform by identifying an S point and T point in the electrical signal waveform and determining a first candidate J point in the electrical signal waveform having substantially a maximum distance from a line between the identified S and T points, the distance being measured perpendicularly to the line.

The present patent document is a divisional of application Ser. No.12/628,659, filed Dec. 1, 2009, which is a non-provisional ofApplication Ser. No. 61/175,616, filed on May 5, 2009, the disclosure ofwhich is hereby incorporated by reference.

FIELD OF THE INVENTION

This invention concerns a system for identifying particular points in anelectrophysiological signal representing heart electrical activity, bydetermining and processing parameters of particular segments of theelectrophysiological signal.

BACKGROUND OF THE INVENTION

An electrocardiogram (ECG) is used by cardiologists to aid in thediagnosis of various cardiac abnormalities. An ECG records heartelectrical activity over a heart cycle as illustrated in FIG. 2 showingfiducial points and segments including ST, QRS and PQ segments. Fiducialpoints are landmarks in an ECG complex signal such as the isoelectricline (PQ junction), and onset of individual waves such as PQRST. Cardiacarrhythmia and ischemia are some of the conditions that are identifiedthrough the analysis of an ECG. There is a strong correlation between STsegment deviation and incidence of ischemia. Also ST deviationmeasurement is an important parameter in clinical study. Some knownsystems employ Wavelet Transforms for ECG signal examination involvingSlope based analysis of a raw ECG signal. These systems are timeconsuming and have problems providing accurate results from noisysignals. A system according to invention principles provides automatedST deviation detection and addresses deficiencies and associatedproblems of known arrangements.

SUMMARY OF THE INVENTION

A system automatically detects and measures ST deviation of a heart waveECG signal in the presence of noise and accommodates baseline variationof the signal and other artefacts. A system identifies a particularpoint in an electrophysiological signal representing heart electricalactivity using an interface for receiving an electrical signal waveformcomprising an R-wave and including an ST segment portion associated withheart electrical activity of a patient over a heart beat cycle. A signalprocessor processes data representing the electrical signal waveform byidentifying an S point and T point in the electrical signal waveform anddetermining a first candidate J point in the electrical signal waveformhaving substantially a maximum distance from a line between theidentified S and T points, the distance being measured perpendicularlyto the line.

In a feature of the invention the signal processor determinesexponential values of data samples of the electrical signal waveformlying between a T peak of a heart cycle and a P peak of a subsequentsuccessive heart cycle. The signal processor identifies particularsamples having a derivative of the determined exponential values below apredetermined threshold value and determines a baseline portion of theelectrical signal waveform in response to the identified particularsamples.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 shows a system for identifying a particular point in anelectrophysiological signal representing heart electrical activity,according to invention principles.

FIG. 2 shows fiducial points and segments of an ECG signal indicatingheart electrical activity over a heart cycle.

FIG. 3 shows an ECG signal indicating heart electrical activity over aheart cycle showing a J point when an S point is present, according toinvention principles.

FIG. 4 shows an ECG signal indicating heart electrical activity over aheart cycle showing a J point when an S point is absent, according toinvention principles.

FIG. 5 similarly illustrates identification of a J point in multipleheart cycles of an ECG signal indicating heart electrical activity,according to invention principles.

FIG. 6 illustrates computation of a baseline of an ECG signal indicatingheart electrical activity over multiple heart cycles, according toinvention principles.

FIG. 7 illustrates S points in multiple heart cycles of an ECG signal,according to invention principles.

FIG. 8 shows a flowchart of a process used by a system for identifying aparticular point in an electrophysiological signal representing heartelectrical activity, according to invention principles.

DETAILED DESCRIPTION OF THE INVENTION

A system automatically detects and measures ST deviation of a heart waveECG signal in the presence of noise in the signal and accommodatesbaseline variation of the signal and other artefacts. FIG. 1 showssystem 10 for identifying a particular point in an electrophysiologicalsignal representing heart electrical activity. Patient monitoring unit15 acquires signal data from patient 12 and processes the acquired databy buffering, filtering, amplification and digitization, for example, toprovide an electrical signal waveform. Interface 19 receives theelectrical signal (e.g., ECG) waveform from unit 15, comprising anR-wave and including an ST segment portion associated with heartelectrical activity of a patient over a heart beat cycle. Interface 19also pre processes the electrical signal to remove noise and baselinevariation using signal filters. Signal processor 27 processes datarepresenting the electrical signal waveform by identifying an R pointusing a peak detection function using one of multiple different knownfunctions. Signal processor 27 processes data representing theelectrical signal waveform by identifying an S point using a knownWavelet transform, for example and a T point in the electrical signalwaveform. Signal processor 27 further determines a first candidate Jpoint in the electrical signal waveform having substantially a maximumdistance from a line between the identified S and T points, the distancebeing measured perpendicularly to the line. Signal processor 27 alsocomputes a baseline of the electrical signal waveform.

FIG. 3 shows an ECG signal indicating heart electrical activity over aheart cycle showing a J point when an S point is present andillustrating identification of a J Point using a Perpendicular Distancemethod. Signal processor 27 processes data representing the electricalsignal waveform by searching for S point 303 of an ECG signal using aWavelet transform, for example. An S point is a fiducial point in an ECGsignal and comprises a first local minimum immediately following an Rpeak (visually it is the first negative peak after an R peak). Signalprocessor 27 determines whether the S point exists and its index if itdoes exist. An S point index is the temporal location of the occurrenceof the S point. In a first signal processing iteration, signal processor27 assumes the S point exists. If the S point exists, signal processor27 projects a line L 305 from S point 303 to T point 307. FIG. 7illustrates S points in multiple heart cycles of an ECG signal.

Signal processor 27 detects a T point 307 by determining a highest point(or peak) of the ECG signal that lies between R+x and R+y values. Signalprocessor 27 takes this highest point as a T point 307 of that heartcycle. In this computation, R is the location of the R peak 313 for theheart cycle concerned, x and y are offsets in millisecond (ms)determined based on Heart Rate (HR). In this embodiment, for HR>120beats per minute (bpm), x=60 ms and y=200 ms and for HR<=120 bpm, x=80ms and y=300 ms. In this embodiment, the values for x and y areempirically determined but in another embodiment may be selected frompredetermined data for a patient having similar demographiccharacteristics (including age, gender, height weight) derived from apopulation of patients. Signal processor 27 determines perpendiculardistances, e.g. 309, from the signal enclosed between S 303 and T 307 toline L 305 as sample values and identifies and records a point in theECG waveform having the largest perpendicular distance as J point 320.FIG. 5 similarly illustrates identification of a J point in multipleheart cycles of an ECG signal indicating heart electrical activity.

Occasionally an S point may not be as distinct as is shown in FIG. 3. Insuch cases signal processor 27 does not detect an S point and proceedswith a workflow for an undetected S point. FIG. 4 shows an ECG signalindicating heart electrical activity over a heart cycle showing J point420 when an S point is absent. In response to analyzing the ECG signaland determining the S point does not exist, signal processor 27 projectsa line L from R point 413 to T point 407 and determines perpendiculardistances, e.g., 409, from the signal enclosed between R and T to line Las sample values and identifies and records a point in the ECG waveformhaving the largest perpendicular distance as J point 420. Signalprocessor 27 improves accuracy of J point detection by performingprocessing of the ECG signal for J point detection using both the methodfor identifying a J point in the presence of an S point and the methodfor identifying a J point in the absence of an S point. Signal processor27 determines a J point identified by either or both methods that liesclosest to a time of 40 ms after an R peak and uses this as a J point.

The J point is often difficult to locate as it typically appears as justa small kink in an ECG signal. Owing to the presence of noise, whichtypically cannot be fully removed by filtering, there are many suchkinks in the region of an expected J point making its detectiondifficult. Further, some signals may not have a prominent J point atall. In such cases, it is necessary to locate a point that best fits thepossible location of a J point. The system addresses these problemsusing a location property of the J point as well the geometry of aneighbouring region. The system advantageously employs a temporalproperty of the J point (for example, the J point should occur atapproximately 40 ms after an R peak) to improve the accuracy of the Jpoint detection.

FIG. 6 illustrates computation of a baseline of an ECG signal indicatingheart electrical activity over multiple heart cycles. In computingbaseline values 603, 605 and 607, for example, for individual heartcycles, signal processor 27 determines T and P peak values.Specifically, for an individual heart cycle 623, for example, signalprocessor 27 determines a T peak value of preceding heart cycle 620 anddetermines a P peak value of current cycle 623. Signal processor 27determines a T peak value in the manner previously described inconnection with FIG. 3. Signal processor 27 determines a P peak value bysearching for a highest point (peak) of the ECG signal preceding an Rpeak between R−x and R−y values. In this computation, R is the locationof the R peak for heart cycle 623, x and y are empirically determinedoffsets in millisecond (ms) determined based on Heart Rate (HR). In thisembodiment, for HR<=120 beats per minute (bpm), x=80 ms and y=200 ms andfor >120 bpm, x=60 ms and y=160 ms.

Further, signal processor 27 determines exponential values of ECG signalsample values between the determined T and P points. The region betweenthe T and P points that qualifies as a baseline shows insignificantslope change and is difficult to detect. Thus signal processor 27advantageously computes an exponential value of the samples valuesbetween the T and P points to exaggerate signal slope change. Theexponential function creates a closer grouping of values for use inidentifying a flattest segment of the signal. Processor 27 determines aderivative of the computed exponential values and determines aconsecutive length of samples that have a derivative value (slopechange) less than an empirically determined threshold (e.g., 0.05).Further, processor 27 determines a mode of the ECG signal values thatbelong to this consecutive length of signal as a baseline.

Signal processor 27 advantageously identifies a J point and computes anECG signal baseline. Known systems typically determine a baseline byidentifying the longest flattest segment between T and P peaks based onslope change. However, ECG signals (especially the region that qualifiesto be the baseline) typically shows insignificant slope changes betweenneighbouring points. System 10 (FIG. 1) addresses these problems, bydetermining the exponential values of ECG signal values and by using theexponential values which exaggerate slope change between neighbouringpoints and make it easily observable.

FIG. 8 shows a flowchart of a process used by system 10 (FIG. 1) foridentifying a particular point in an electrophysiological signalrepresenting heart electrical activity. In step 812 following the startat step 811 interface 19 receives an electrical signal waveformcomprising an R-wave and including an ST segment portion and T point andP point peaks associated with heart electrical activity of a patientover multiple heart beat cycles. In step 815 signal processor 27processes data representing the electrical signal waveform byidentifying an S point value and R point value in the electrical signalwaveform and in step 817 identifies a T point peak value in a firstheart cycle in the electrical signal waveform. In step 819 processor 27determines a first candidate J point in the electrical signal waveformhaving substantially a maximum distance from a line between theidentified S and T points, the distance being measured perpendicularlyto the line. Processor 27 processes data representing the electricalsignal waveform by determining a second candidate J point in theelectrical signal waveform having substantially a maximum distance froma second line between the identified R and T points, the distance beingmeasured perpendicularly to the second line. Processor 27 selects theclosest of the first and second candidate J points to a pointsubstantially 40 milliseconds after the R point. The selected J point isused for further analysis.

The determined J point identifies the start of an ST segment andprocessor 27 uses the identified J point in computing ST segmentvariation from the electrical signal waveform baseline and in responseto the variation exceeding a predetermined threshold value, initiatesgeneration of an alert message to a worker. Signal processor 27determines J points for individual heart cycles of multiple sequentialcycles and uses the identified J points in computing ST correspondingsegment values for individual heart cycles of the multiple sequentialcycles.

Processor 27 in step 824 identifies a P peak point of a second heartcycle subsequent and successive to the first heart cycle in theelectrical signal waveform and in step 827 determines exponential valuesof data samples of the electrical signal waveform lying between theidentified T and P peak points. In step 830, processor 27 identifiesparticular samples having a derivative of the determined exponentialvalues below a predetermined threshold value and in step 833 determinesa baseline portion of the electrical signal waveform in response to theidentified particular samples. Specifically, processor 27 processes datarepresenting the electrical signal waveform by determining a baselineportion of the electrical signal waveform as a portion having thelargest number of consecutive identified particular samples. Also,processor 27 computes an ST segment value and variation of the STsegment value from the determined baseline portion of the electricalsignal waveform and in response to the variation exceeding apredetermined threshold value, initiates generation of an alert messageto a worker, indicating ischemia, for example. Processor 27 determineselectrical signal waveform baseline values for individual heart cyclesand computes ST segment variation from the electrical signal waveformbaseline values for individual heart cycles. The process of FIG. 8terminates at step 836.

A processor as used herein is a computer, processing device, logic arrayor other device for executing machine-readable instructions stored on acomputer readable medium, for performing tasks and may comprise any oneor combination of, hardware and firmware. A processor may also comprisememory storing machine-readable instructions executable for performingtasks. A processor acts upon information by manipulating, analyzing,modifying, converting or transmitting information for use by anexecutable procedure or an information device, and/or by routing theinformation to an output device. A processor may use or comprise thecapabilities of a controller or microprocessor, for example, and isconditioned using executable instructions to perform special purposefunctions not performed by a general purpose computer. A processor maybe coupled (electrically and/or as comprising executable components)with any other processor enabling interaction and/or communicationthere-between. A display processor or generator is a known elementcomprising electronic circuitry or software or a combination of both forgenerating display images or portions thereof.

An executable application, as used herein, comprises code or machinereadable instructions for conditioning the processor to implementpredetermined functions, such as those of an operating system, a contextdata acquisition system or other information processing system, forexample, in response to user command or input. An executable procedureis a segment of code or machine readable instruction, sub-routine, orother distinct section of code or portion of an executable applicationfor performing one or more particular processes. These processes mayinclude receiving input data and/or parameters, performing operations onreceived input data and/or performing functions in response to receivedinput parameters, and providing resulting output data and/or parameters.A user interface (UI), as used herein, comprises one or more displayimages, generated by a display processor and enabling user interactionwith a processor or other device and associated data acquisition andprocessing functions.

The UI also includes an executable procedure or executable application.The executable procedure or executable application conditions thedisplay processor to generate signals representing the UI displayimages. These signals are supplied to a display device which displaysthe image for viewing by the user. The executable procedure orexecutable application further receives signals from user input devices,such as a keyboard, mouse, light pen, touch screen or any other meansallowing a user to provide data to a processor. The processor, undercontrol of an executable procedure or executable application,manipulates the UI display images in response to signals received fromthe input devices. In this way, the user interacts with the displayimage using the input devices, enabling user interaction with theprocessor or other device. The functions and process steps herein may beperformed automatically or wholly or partially in response to usercommand. An activity (including a step) performed automatically isperformed in response to executable instruction or device operationwithout user direct initiation of the activity.

The system and processes of FIGS. 1-8 are not exclusive. Other systems,processes and menus may be derived in accordance with the principles ofthe invention to accomplish the same objectives. Although this inventionhas been described with reference to particular embodiments, it is to beunderstood that the embodiments and variations shown and describedherein are for illustration purposes only. Modifications to the currentdesign may be implemented by those skilled in the art, without departingfrom the scope of the invention. The system automatically detects andmeasures ST segment deviation of a heart wave ECG signal, for example,from a baseline in the presence of noise in the signal and accommodatesbaseline variation of the signal between heart cycles and accommodatesother artefacts. Further, the processes and applications may, inalternative embodiments, be located on one or more (e.g., distributed)processing devices on a network linking the units of FIG. 1. Any of thefunctions and steps provided in FIGS. 1-8 may be implemented inhardware, software or a combination of both.

What is claimed is:
 1. A system for identifying a particular point in anelectrophysiological signal representing heart electrical activity,comprising: an interface for receiving an electrical signal waveformcomprising T peaks and P peaks associated with heart electrical activityof a patient over a plurality of heart beat cycles; and a signalprocessor for processing data representing said electrical signalwaveform by (a) determining exponential values of data samples of saidelectrical signal waveform lying between a T peak of a heart cycle and aP peak of a subsequent successive heart cycle, (b) identifyingparticular samples having a derivative of the determined exponentialvalues below a predetermined threshold value, (c) determining a baselineportion of said electrical signal waveform in response to the identifiedparticular samples, (d) computing ST segment variation from thedetermined baseline portion of said electrical signal waveform, and (e)in response to the variation exceeding a predetermined threshold value,initiating generation of an alert message.
 2. A system according toclaim 1, wherein said signal processor processes data representing saidelectrical signal waveform by (i) identifying a T peak point in saidelectrical signal waveform and (ii) identifying a P peak point in saidelectrical signal waveform.
 3. A system according to claim 1, whereinsaid signal processor determines the start of an ST segment byidentifying a point in said electrical signal waveform havingsubstantially a maximum distance from a line between S and T points,said distance being measured perpendicular to said line and said signalprocessor uses the identified point in computing ST segment variationfrom said electrical signal waveform baseline and in response to thevariation exceeding a predetermined threshold value, initiatesgeneration of an alert message to a worker.
 4. A system for identifyinga particular point in an electrophysiological signal representing heartelectrical activity, comprising: an interface for receiving anelectrical signal waveform comprising T peaks and P peaks associatedwith heart electrical activity of a patient over a plurality of heartbeat cycles; and a signal processor for processing data representingsaid electrical signal waveform by (a) identifying a T peak point of afirst heart cycle in said electrical signal waveform, (b) identifying aP peak point of a second heart cycle subsequent and successive to saidfirst heart cycle in said electrical signal waveform, (c) determiningexponential values of data samples of said electrical signal waveformlying between the identified T and P peak points, (d) identifyingparticular samples having a derivative of the determined exponentialvalues below a predetermined threshold value, (e) determining a baselineportion of said electrical signal waveform in response to the identifiedparticular samples, (f) computing ST segment variation from thedetermined baseline portion of said electrical signal waveform, and (g)in response to the variation exceeding a predetermined threshold value,initiating generation of an alert message.
 5. A system according toclaim 4, wherein said signal processor processes data representing saidelectrical signal waveform by determining a baseline portion of saidelectrical signal waveform as a portion having the largest number ofconsecutive identified particular samples.
 6. A system according toclaim 4, wherein said signal processor determines the start of an STsegment by identifying a point in said electrical signal waveform havingsubstantially a maximum distance from a line between S and T points,said distance being measured perpendicularly to said line and saidsignal processor uses the identified point in computing ST segmentvariation from said electrical signal waveform baseline and in responseto the variation exceeding a predetermined threshold value, initiatesgeneration of an alert message to a worker.
 7. A system according toclaim 4, wherein said signal processor determines electrical signalwaveform baseline values for individual heart cycles and computes STsegment variation from said electrical signal waveform baseline valuesfor individual heart cycles.